International audienceWe developed a parallel time domain decomposition method to solve systems of ODEs based on the Aitken-Schwarz domain decomposition method only in time (Linel P, Tromeur-Dervout D. Aitken-Schwarz and schur complement methods for time domain decomposition. In: Parallel computing: from multicores and GPU's to Petascale. Advances in parallel computing, vol. 19; 2010. p. 75-82). The method transforms the initial time value problem into a time boundary values problem. This paper details the proof of the pure linear convergence of this DDM in case of linear system of ODEs and provides an optimized MPI parallel implementation when a regular size splitting of the time interval is performed. Then an extension of the method to th...
. Time dependent partial differential equations are often solved using algorithms which parallelize ...
We present a parallel solution algorithm for the transient heat equation in one and two spatial dime...
Abstract. PDE-constrained optimization problems have a wide range of applications, but they lead to ...
International audienceWe developed a parallel time domain decomposition method to solve systems of O...
International audienceNew parallel methods, based on the Schwarz and Schur domain decomposition tech...
International audienceNew parallel methods, based on the Schwarz and Schur domain decomposition tech...
International audienceNew parallel methods, based on the Schwarz and Schur domain decomposition tech...
Les méthodes de décomposition de domaine en espace ont prouvé leur utilité dans le cadre des archite...
Les méthodes de décomposition de domaine en espace ont prouvé leur utilité dans le cadre des archite...
Abstract. With the continued evolution of computing architectures towards many-core com-puting, algo...
Domain decomposition methods in space applied to Partial Differential Equations (PDEs) expanded cons...
International audienceOptimizing solvers for linear systems is a major challenge in scientific comp...
International audienceOptimizing solvers for linear systems is a major challenge in scientific comp...
summary:We present a parallel solution algorithm for the transient heat equation in one and two spat...
summary:We present a parallel solution algorithm for the transient heat equation in one and two spat...
. Time dependent partial differential equations are often solved using algorithms which parallelize ...
We present a parallel solution algorithm for the transient heat equation in one and two spatial dime...
Abstract. PDE-constrained optimization problems have a wide range of applications, but they lead to ...
International audienceWe developed a parallel time domain decomposition method to solve systems of O...
International audienceNew parallel methods, based on the Schwarz and Schur domain decomposition tech...
International audienceNew parallel methods, based on the Schwarz and Schur domain decomposition tech...
International audienceNew parallel methods, based on the Schwarz and Schur domain decomposition tech...
Les méthodes de décomposition de domaine en espace ont prouvé leur utilité dans le cadre des archite...
Les méthodes de décomposition de domaine en espace ont prouvé leur utilité dans le cadre des archite...
Abstract. With the continued evolution of computing architectures towards many-core com-puting, algo...
Domain decomposition methods in space applied to Partial Differential Equations (PDEs) expanded cons...
International audienceOptimizing solvers for linear systems is a major challenge in scientific comp...
International audienceOptimizing solvers for linear systems is a major challenge in scientific comp...
summary:We present a parallel solution algorithm for the transient heat equation in one and two spat...
summary:We present a parallel solution algorithm for the transient heat equation in one and two spat...
. Time dependent partial differential equations are often solved using algorithms which parallelize ...
We present a parallel solution algorithm for the transient heat equation in one and two spatial dime...
Abstract. PDE-constrained optimization problems have a wide range of applications, but they lead to ...